Change detection

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Contents

Prerequisites of spatio-temporal image analysis

Correct the pixel intensities as much as possible for uninteresting differences:

  1. Sensor calibration
  2. Exact spatial co-registration of images (especially pixel-by-pixel comparision)
  3. Cloud and cloud shadow masking
  4. Haze reduction
  5. Atmospheric correction
  6. Topographic illumination correction (mountains)
  7. Clear definitions and classification scheme

Visualization of multi-temporal images

  1. Add subsets of 3 Landsat TM multispectral scenes of 1992 (SUB_LT4_1992-07-30_MUL.tif), 2006 (SUB_LT5_2006-06-11_MUL.tif)and 2010 (SUB_LT5_2010-07-08_MUL.tif) into the QGIS TOC.
  2. Create color composites RGB=(B5 SWIR-1),(B4 NIR), (B3 Red) following Changing Raster Layer Style of a multiband file.
  3. Select Web --> OpenLayers plugin --> Google Maps --> Google Satellite.
If the Plugin doesn't exist you'll first have to install the Openlayers plugin using Plugins --> Manage and install plugins.

A new Layer Google Maps is loaded into the layers window. The project CRS is automatically set to WGS84/Pseudo Mercator (EPSG:3857). Drag and drop the Layer to the bottom of the TOC.

Globe plugin

  • The Globe plugin is already installed. It just needs to be activated.

Plugins --> Manage and Install Plugins --> Installed. Click the checkbox or doubleclick the name Globe to activate the plugin.

  • Plugins --> Globe --> Launch Globe. The Globe windows opens side by side to the map canvas.
  • In the Globe viewer click on Globe settings Qgis globe settings.png. Switch off the atmosphere rendering by unchecking the box Sky. OK.
  • Adjust the size of the Globe viewer to the same size as the map canvas.
  • In the map canvas zoom in to a region of interest. Adjust the local histogram stretch for all layers in the TOC clicking Example.jpg (Raster Tools).

MapSwipe plugin

Temporal/Spectral Profile plugin

Change detection techniques

Bitemporal

Post-classification Comparison

Two co-registered satellite images are independently classified to yield thematic maps. Discrete class labels are compared to determine changes using cross-tabulation in which all transitions are presented. Use the Semi Automatic Classification plugin: Postprocessing --> Land cover change

Raster algebra: Difference

  1. Add subsets of multispectral 2 Landsat TM images of 1992 (SUB_LT4_1992-07-30_MUL.tif) and 2010 (SUB_LT5_2010-07-08_MUL.tif) into a the QGIS TOC project.


Raster algebra: Ratio

  1. Open Toolbox --> OTB --> Feature Extraction --> Radiometric indices.
    • Set tm_920526_mul.tif as Input Image.
    • Set Red Channel to 4 and NIR Channel to 5.
    • Set Available Radiometric Indices to ndvi.
    • Save the Output Image as ndvi1992.
    • Repeat this procedure for the raster file of 2005 and adapt the name of the Output Image to ndvi_2005.
  2. Calculate the ratio of both raster images with the Raster --> Raster Calculator.
    • Choose ndvi_2005 from the Raster bands by double clicking on the raster name.
    • Choose the division operator from the Operators by clicking on /.
    • Choose ndvi_1992.tif from the Raster bands by double clicking on the raster name.
    • Save the Output layer as ndvi_ratio and press OK.

Multi-temporal

Multi-temporal color composites

  1. Add the raster layers of the years 1992 (tm_920526_mul.tif), 2000 (etm_000515_mul.tif) and 2005 (etm_050623_mul.tif) into a QGIS project. It should be available in the course data.
  2. Open Toolbox --> OTB --> Miscellaneous --> Band Math.
  3. Calculate the amplitude for each raster layer (1992, 2000, 2005) with the use of the bands 5-4-3.
    • For the year 1992, set tm_920526_mul.tif as Input image list.
    • Type sqrt(im1b4^2 + im1b5^2 + im1b3^2) as Expression.
    • Save theOutput image as amplitude1992.
    • Repeat this procedure for the raster files of 2000 and 2005 and adapt the name of each Output Raster File.
  4. Merge the three output raster files with Toolbox --> GDAL/OGR --> [GDAL] Miscellaneous --> Merge
  5. Load the three amplitude****.tif files as Input Layers, mark Layer Stack and save Merged output as amplitude_merge.

Multi temporal.png

Principal component analysis

  1. Add the raster layers of the years 1992 (tm_920526_mul.tif), 2000 (etm_000515_mul.tif) and 2005 (etm_050623_mul.tif) into a QGIS project. It should be available in the course data.
  2. Install PCA plugin under Plugins --> Manage and Install Plugins....
  3. Open PCA plugin Pca.png.
    • Set tm_920526_mul.tif as Input Raster File.
    • Set Number of output Principal Components to 1.
    • Save the Output Raster File as pca1992_1.
    • Repeat this procedure for the raster files of 2000 and 2005 and adapt the name of each Output Raster File.
  4. Merge the three output raster files with Toolbox --> GDAL/OGR --> [GDAL] Miscellaneous --> Merge.
  5. Load the three pca****_1.tif files as Input Layers, mark Layer Stack and save Merged output as pca_merge.
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